The present invention relates to medical monitoring methods and devices and, in particular, it concerns a method and device for monitoring the depth of anesthesia (DOA) during surgery.
It is known that monitoring of the depth of anesthesia during a surgical procedure is necessary so as to ensure both the comfort and safety of the patient, as well as a controlled surgical field for the surgeon. Current anesthetic practice is that the anesthesiologist infers the depth of anesthesia by observing several measured physiological variables, such as the patient's heart rate, systolic and diastolic blood pressure, and a photoplethysmographic (PPG) blood pressure waveform signal. Changes in these variables in response to surgical cuts or manipulations are interpreted by the anesthesiologist as indicating a level of anesthesia that is either adequate or inadequate. It is well known, however, that multiple factors, besides the DOA, may influence an individual patient's physiological response to a surgical stress, and that none of the above mentioned physiological variables, either singly or in combination, provide a truly objective indication of the DOA. As such, evaluation of the DOA by standard contemporary practice is an imprecise art, dependent on the knowledge and prior experience of the anesthesiologist. Furthermore, as the anesthesiologist is required to monitor and interpret the display readouts of several physiological variables simultaneously so as to evaluate the patient's DOA, the ongoing evaluation of the DOA, by standard contemporary practice, is a laborious procedure.
There has thus been much interest in developing sophisticated and automatic DOA monitors that could automatically and reliably monitor the DOA on an ongoing basis during a surgical procedure. To date, such devices have largely been based on the measurement of electrophysiological signals such as electrocardiographic (ECG) signals, electroencephalographic (EEG) signals, auditory and somatosensory evoked potentials, and craniofacial electromographic (EMG) signals. As all of the above biophysiological parameters involve measurable electric currents, they are hereinafter referred to as "electrically active" biological parameters, and are to be distinguished from those biological parameters which are not mediated by measurable electric currents, such as body temperature, blood pressure and other hemodynamic variables, which are hereinafter referred to as "electrically passive" biological parameters.
Analysis of electrically active parameters for the purpose of monitoring DOA has been found to be cumbersome and unreliable. Specifically, bispectral analysis of EEG signals (resulting in an index of anaesthetic depth known as the bispectral index), and other EEG-based parameters, have been shown to be unreliable predictors of DOA [Katoh T, Suzuki A, Ikeda K: Electroencephalographic Derivatives as a Tool for Predicting the Depth of Sedation and Anesthesia Induced by Sevoflurane. Anesthesiology 1998 Mar; 88 (3):642-650]. Furthermore, Thomsen et al. found that EEG based methods are particularly unreliable at deeper levels of anesthesia, when burst suppression patterns may occur on the EEG [Thomsen C E, Prior P: Quantitative EEG in Assessment of Anesthesia Depth. Methods of comparison. Ugeskr Laeger 1998 Feb 23;160 (9): 1323-1329].
A method for objectively and continuously determining the DOA of a patient during surgery would allow the anesthesiologist to administer the minimal dose of anesthetic required to achieve the desired DOA, thus minimizing anesthesia-related side effects. Furthermore, such a method would enable less experienced anesthesiologists to administer anesthesia in a more reliable and effective manner. There is therefore a need for, and it would be highly advantageous to have, a method for monitoring a patient's DOA, which is automatic, and not based on standard electrophysiological signal processing techniques.